The Agricultural Ontology Service AOS

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• The Agricultural Ontology Service(AOS)
• Effort for Content Standardization in Agriculture
• Frehiwot Fisseha (UNFAO)
• Frehiwot.Fisseha_at_fao.org

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Outline

• FAOs mandate in agricultural information
  management
• Problems we want to solve
• The current situation
• Proposed solution
• The Agricultural Ontology Service (AOS)
• AOS prototype (The Fishery Ontology Service)

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FAOs mandate

• FAOs main goal is to reduce the number of hungry
  people by 50 within the year 2015.
• WAICENT (World Agricultural Information Center)
  is FAOs approach to fight hunger with
  information.
• FAO produces a huge amount of data/information in
  agriculture and related disciplines.
• It is also within FAOs mandate to make available
  agriculture related information from other
  information providers.
• FAO collaborates in information networks which
  are dedicated to the dissemination of
  agricultural domain.

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Problems we want to solve
The Information Organization problem faced by
Information Managers At present most
information management tasks are performed
manually. ... consider the cataloging and
indexing task. Manual cataloging and indexing
are labor-intensive processes, requiring special
training. Tools for automating or
semi-automating these processes are much in
demand.
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Problems we want to solve
The Information Retrieval problem faced by
Information Users

• Both parameters are ranking low today!

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Problems we want to solve

• Topic Trees from categorization schemes and
  thesauri are rigid and not very expressive

• Machine produced clusters are flexible, but
  imprecise and at times out of context

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Knowledge Organizations Systems Metadata Schema

• The subject categorization schemes are not
  adequately developed to be of use for semantic
  description for web resources
• The metadata schemas are closely attached to
  traditional description of bibliographical
  records
• The Dublin Core Metadata Initiative (DCMI) is a
  step forward to define core metadata to describe
  information objects
• Effort is underway to develop Agricultural
  metadata standards

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Knowledge Organization Systems Vocabularies

• Insufficient subject language coverage

Existing Thesauri and Knowledge Organization
Systems (KOSs)
Dedicated KOSs
e.g., ASFA thesaurus
e.g., the Multilingual Forestry Thesaurus

• Only very simple encoding of semantic relations

e.g., the Sustainable Development website
classification

• Common concepts are not declared

e.g., biological taxonomies such as NCBI and ITIS

• No or very limited interoperability

Other thematic thesauri
Non-dedicated KOSs

• Very limited machine readability

CABI Thesaurus
AGROVOC
NAL Thesaurus

• Severe maintenance problems

GEMET
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Some observations

• No cross navigation between applications
• Full text search engines based on statistical
  text analysis are imprecise
• Systems based only on machine intelligence do
  not show too promising results
• Web crawlers and harvesters do good jobs only on
  already structured information sources.
• Recognition of meaning (semantic analysis) by
  machines is only possible by using using
  structured meta-information and formal knowledge
  description
• Agreed metadata schemas
• Controlled vocabularies, Taxonomies

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The solution we propose- Domain Ontology

• An ontology is a formal knowledge organization
  system
• A formal description of the application knowledge
• It contains concepts and their definitions
• Relations between concepts
• Possibility for machine processing

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What benefits do we expect from Ontology?

• Semantic Organization of websites
• Knowledge maps
• Guided discovery of knowledge
• Easy retrievability of information without using
  complicated Boolean logic
• Text processing by machines
• Text Mining on the Web (meaning-oriented
  access)
• Automatic indexing and text annotation tools
• Full text search engines that create meaningful
  classification (FAO-Schwartz not related to FAO)
  (semantic clustering)
• Intelligent search of the Web
• Building dynamical catalogues from machine
  readable meta data
• Cross Domain Search
• Natural Language processing
• Better machine translation
• Queries using natural language

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Guided Browse and Search Facilities
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Context Sensitive Knowledge Access
Agricultural Web Page
Use your right mouse button to learn more about
an italicized word on the page.
Biosecurity management of all biological and
environmental risks associated with food and
agriculture, including forestry and
fisheries See also Biosafety Food Safety Risk
Management Or are you interested in... Food
Security Biological Diversity
Conservation agriculture Farmers like it because
it gives them a means of conserving, improving
and making more efficient use of their natural
resources About camels and llamas Descendants of
the same rabbit-sized mammal, they have become
two of humanity's most versatile domestic animals
Agribusiness and small farmers Well managed
contract farming contributes to both increased
income for producers and higher profits for
investors Toward biosecurity Biological and
environmental risks associated with food and
agriculture have intensified with economic
globalization Urban food marketing In the
century of cities, a major challenge will be
providing adequate quantities of nutritional and
affordable food for urban inhabitants Crop
science and ethics In order to continue their
contribution to human development, crop
scientists must regain credibility
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The Collaborative Approach We Want to Adopt

• Only agreed semantic standards guarantee
  knowledge discovery between different
  applications.
• Developing Knowledge Organization Systems is
  resource intensive and requires stakeholders
  agreement and participation.
• Hence, FAO started initiatives to bring
  interested partners together
• The AGStandards initiative was launched in
  October, 2000 to agree on agricultural metadata
  standards
• The Agricultural Ontology Service (AOS) concept
  paper was publicized in July 2001.

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What does Agricultural Ontology Service mean?

• The Agricultural Ontology Service is an approach
  to organize knowledge organization systems that
  is
• International
• The Internet must become multilingual
• Multidisciplinary
• The field of agriculture is broad and
  multidisciplinary.
• Cooperative
• Stakeholders can contribute different expert
  knowledge
• Distributed
• No central ownership
• Coordinated
• Coordination must ensure reusability and
  standardization

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AOS Iterative Knowledge Registration
Components terms, definitions, relationships
KOS uses components to build an application
Agricultural Ontology Service (AOS) Federated
storage and description facility
Components terms, definitions, relationships
Discussions and choices for amendments to
components
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Activities to date

• The first AOS workshop took place in Rome,
  November 2001
• A launch group was established with participation
  of
• Content providers (FAO, CABI)
• Solution providers in the Agricultural Area (ATO
  -Wageningen, University of Florida)
• Ontology development Groups (AIFB Karlsruhe, CNR
  Italy)
• Ontology experts
• The second AOS workshop (January 2002 in Oxford)
• Decision to develop prototypes as proof of
  concept.
• The Fishery Ontology Service (FOS) is one of the
  prototypes
• The third AOS workshop took (May 2002 Florida)
• Decision to setup the AOS consortium

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AOS a business model

• A consortium of Information Providers
• A clearinghouse for semantic standards in
  agriculture and related discipline.
• One stop access to agreed standards (Ontologies,
  Metadata schemas, Vocabularies).
• Participation as a consortium in semantic web
  activities (Ontoweb).
• Organization of seminars and workshops to further
  develop and promote the use of semantic
  standards.

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AOS Prototype-The Fishery Ontology Service (FOS)

• Goal to integrate the multilingual fishery and
  aquatic resources terminology
• the oneFish Community Directory,
• ASFA,
• FIGIS,
• AGROVOC
• Objective
• to have a better tool for document indexing and
  information retrieval,
• to promote interaction and knowledge sharing
  within the fishery community